How to disable exceptions encountered when calling Lambda layer?

I’m experimenting with some logic before creating a custom keras layer, but my Lambda layer isn’t allowing me to check the output shape with model.summary(). It says:

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ValueError: Exception encountered when calling layer “Lambda_1” (type Lambda).

The following Variables were created within a Lambda layer (Lambda_1)

but are not tracked by said layer:

<tf.Variable ‘Lambda_1/map/while/RGAT_1/edge_type_0/kernel:0’ shape=(7, 10) dtype=float32>

<tf.Variable ‘Lambda_1/map/while/RGAT_1/edge_type_0/Edge_attention_parameters_0:0’ shape=(5, 4) dtype=float32>

The layer cannot safely ensure proper Variable reuse across multiple

calls, and consquently this behavior is disallowed for safety. Lambda

layers are not well suited to stateful computation; instead, writing a

subclassed Layer is the recommend way to define layers with

Variables.

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Is there a way to temporally disable this behavior? 🤔